Comparing Rates of Undiagnosed Hypertension and Diabetes in Patients With and Without Substance Use Disorders.

BACKGROUND: Individuals with substance use disorders (SUDs) have increased risk for developing chronic conditions, though few studies assess rates of diagnosis of these conditions among patients with SUDs. OBJECTIVE: To compare rates of undiagnosed hypertension and diabetes among patients with and without an SUD. DESIGN: Cross-sectional analysis using electronic health record (EHR) data from 58 primary care clinics at a large, urban, healthcare system in New York. PARTICIPANTS: Patients who had at least two primary care visits from 2019-2022 were included in our patient sample. Patients without an ICD-10 hypertension diagnosis or prescribed hypertension medications and with at least two blood pressure (BP) readings ≥ 140/90 mm were labeled 'undiagnosed hypertension,' and patients without a diabetes diagnosis or prescribed diabetes medications and with A1C/hemoglobin ≥ 6.5% were labeled 'undiagnosed diabetes.' MAIN MEASURES: We calculated the mean number of patients with and without an ICD-10 SUD diagnosis who were diagnosed and undiagnosed for each condition. We used multivariate logistic regression to assess the association between being undiagnosed for each condition, and having an SUD diagnosis, patient demographic characteristics, clinical characteristics (body mass index, Elixhauser comorbidity count, diagnosed HIV and psychosis), the percentage of visits without a BP screening, and the total number of visits during the time period. KEY RESULTS: The percentage of patients with undiagnosed hypertension (2.74%) and diabetes (22.98%) was higher amongst patients with SUD than patients without SUD. In multivariate models, controlling for other factors, patients with SUD had significantly higher odds of having undiagnosed hypertension (OR: 1.81; 95% CI: 1.48, 2.20) and undiagnosed diabetes (OR: 1.93; 1.72, 2.16). Being younger, female, and having an HIV diagnosis was also associated with significantly higher odds for being undiagnosed. CONCLUSIONS: We found significant disparities in rates of undiagnosed chronic diseases among patients with SUDs, compared with patients without SUDs.

Initiatives to Support the Transition of Patients With Substance Use Disorders From Acute Care to Community-based Services Among a National Sample of Nonprofit Hospitals.

BACKGROUND: Hospitals are a key touchpoint to reach patients with substance use disorders (SUDs) and link them with ongoing community-based services. Although there are many acute care interventions to initiate SUD treatment in hospital settings, less is known about what services are offered to transition patients to ongoing care after discharge. In this study, we explore what SUD care transition strategies are offered across nonprofit US hospitals. METHODS: We analyzed administrative documents from a national sample of US hospitals that indicated SUD as a top 5 significant community need in their Community Health Needs Assessment reports (2019-2021). Data were coded and categorized based on the nature of described services. We used data on hospitals and characteristics of surrounding counties to identify factors associated with hospitals' endorsement of transition interventions for SUD. RESULTS: Of 613 included hospitals, 313 prioritized SUD as a significant community need. Fifty-three of these hospitals (17%) offered acute care interventions to support patients' transition to community-based SUD services. Most (68%) of the 53 hospitals described transition strategies without further detail, 23% described scheduling appointments before discharge, and 11% described discussing treatment options before discharge. No hospital characteristics were associated with offering transition interventions, but such hospitals were more likely to be in the Northeast, in counties with higher median income, and states that expanded Medicaid. CONCLUSIONS: Despite high need, most US hospitals are not offering interventions to link patients with SUD from acute to community care. Efforts to increase acute care interventions for SUD should identify and implement best practices to support care continuity.

Rural-urban disparities in the availability of hospital-based screening, medications for opioid use disorder, and addiction consult services.

INTRODUCTION: Hospitals are an ideal setting to stage opioid-related interventions with patients who are hospitalized due to overdose or other substance use-related complications. Transitional opioid programs-which initiate care and provide linkages upon discharge, such as screening, initiation of medications for opioid use disorder, and addiction consult services-have become the gold standard, but implementation has been uneven. The purpose of this study was to assess disparities in the availability of hospital-based transitional opioid programs, across rural and urban hospital settings in the United States. METHODS: Using hospital administrative data paired with county-level demographic data, we conducted bivariate and regression analyses to assess rural-urban differences in the availability of transitional opioid services including screening, addiction consult services, and MOUD in U.S general medical centers, controlling for hospital- and community-level factors. Our sample included 2846 general medical hospitals that completed the 2021 American Hospital Association (AHA) Annual Survey of Hospitals. Our primary outcomes were five self-reported measures: whether the hospital provided screening in the ED; provided screening in the inpatient setting; whether the hospital provided addiction consult services in the ED; provided addiction consult services in the inpatient setting; and whether the hospital provided medications for opioid use disorder. RESULTS: Rural hospitals did not have lower odds of screening for OUD or other SUDs than urban hospitals, but both micropolitan rural counties and noncore rural counties had significantly lower odds of having addiction consult services in either the ED (OR: 0.74, 95 % CI: 0.58, 0.95; OR: 0.68, 95 % CI: 0.50, 0.91) or inpatient setting (OR: 0.76, 95 % CI: 0.59, 0.97; OR: 0.68, 95 % CI: 0.50, 0.93), respectively, or of offering MOUD (OR: 0.69, 95 % CI: 0.52, 0.90; OR: 0.52, 95 % CI: 0.37, 0.74). CONCLUSIONS: Our study suggests that evidence-based interventions, such as medications for opioid use disorder and addiction consult services, are less often available in rural hospitals, which may contribute to rural-urban disparities in health outcomes secondary to OUD. A priority for population health improvement should be developing implementation strategies to support rural hospital adoption of transitional opioid programs.

Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System.

INTRODUCTION/OBJECTIVE: Previous studies have evaluated the implementation of standardized social determinants of health (SDOH) screening within healthcare settings, however, less is known about where screening gaps may exist following initial implementation based on facility characteristics. The objective of this study is to assess differences in screening rates for SDOH at a large, urban healthcare system. METHODS: We used electronic health record data obtained from NYC Health + Hospitals primary care sites from 2019 to 2022. We calculated the mean number of visits that were SDOH screened by visit type, facility size, and the percentages of community characteristics. We conducted 4 logistic regression models predicting the odds of screening for any SDOH and for specific SDOH needs (housing, food, and medical cost assistance) based on facility type, facility size, and the socioeconomic characteristics of the surrounding community. RESULTS: Among the 3 212 650 visits included, 16.90% were SDOH screened. Across all 4 multivariate logistic regression models predicting SDOH screening, a visit had significantly lower odds of being screened if based at a midsize or small facility, if it was a telemedicine visit, or based at a facility located in a zip-code with a higher percentage of SDOH needs. CONCLUSIONS: Our study found important differences in SDOH screening rates at a large, NYC-based health system based on size, visit type, and community level characteristics. In particular, our findings point to barriers related to facility size and telemedicine workflow that should be addressed to increase uptake of SDOH screening within different visits and facility types.

Uses of Social Determinants of Health Data to Address Cardiovascular Disease and Health Equity: A Scoping Review.

Background Cardiovascular disease is the leading cause of morbidity and mortality worldwide. Prior research suggests that social determinants of health have a compounding effect on health and are associated with cardiovascular disease. This scoping review explores what and how social determinants of health data are being used to address cardiovascular disease and improve health equity. Methods and Results After removing duplicate citations, the initial search yielded 4110 articles for screening, and 50 studies were identified for data extraction. Most studies relied on similar data sources for social determinants of health, including geocoded electronic health record data, national survey responses, and census data, and largely focused on health care access and quality, and the neighborhood and built environment. Most focused on developing interventions to improve health care access and quality or characterizing neighborhood risk and individual risk. Conclusions Given that few interventions addressed economic stability, education access and quality, or community context and social risk, the potential for harnessing social determinants of health data to reduce the burden of cardiovascular disease remains unrealized.

Stakeholder Perspectives on Data-Driven Solutions to Address Cardiovascular Disease and Health Equity in New York City.

Introduction: There is growing recognition of the importance of addressing the social determinants of health in efforts to improve health equity. In dense urban environments such as New York City, disparities in chronic health conditions (e.g., cardiovascular disease) closely mimic inequities in social factors such as income, education, and housing. Although there is a wealth of data on these social factors in New York City, little is known about how to rapidly use available data sources to address health disparities. Methods: Semistructured interviews were conducted with key stakeholders (N=11) from across the public health landscape in New York City (health departments, healthcare delivery systems, and community-based organizations) to assess perspectives on how social determinants of health data can be used to address cardiovascular disease and health equity, what data-driven tools would be useful, and challenges to using these data sources and developing tools. A matrix analysis approach was used to analyze the interview data. Results: Stakeholders were optimistic about using social determinants of health data to address health equity by delivering holistic care, connecting people with additional resources, and increasing investments in under-resourced communities. However, interviewees noted challenges related to the quality and timeliness of social determinants of health data, interoperability between data systems, and lack of consistent metrics related to cardiovascular disease and health equity. Conclusions: Future research on this topic should focus on mitigating the barriers to using social determinants of health data, which includes incorporating social determinants of health data from other sectors. There is also a need to assess how data-driven solutions can be implemented within and across communities and organizations.

Trends in the Prioritization and Implementation of Substance Use Programs by Nonprofit Hospitals: 2015-2021.

OBJECTIVES: Hospitalizations are an important opportunity to address substance use through inpatient services, outpatient care, and community partnerships, yet the extent to which nonprofit hospitals prioritize such services across time remains unknown. The objective of this study is to examine trends in nonprofit hospitals' prioritization and implementation of substance use disorder (SUD) programs. METHODS: We assessed trends in hospital prioritization of substance use as a top five community need and hospital implementation of SUD programing at nonprofit hospitals between 2015 and 2021 using two waves (wave 1: 2015-2018; wave 2: 2019-2021) by examining hospital community benefit reports. We utilized t or χ 2 tests to understand whether there were significant differences in the prioritization and implementation of SUD programs across waves. We used multilevel logistic regression to evaluate the relation between prioritization and implementation of SUD programs, hospital and community characteristics, and wave. RESULTS: Hospitals were less likely to have prioritized SUD but more likely to have implemented SUD programs in the most recent 3 years compared, even after adjusting for the local overdose rate and hospital- and community-level variables. Although most hospitals consistently prioritized and implemented SUD programs during the 2015-2021 period, a 11% removed and 15% never adopted SUD programs at all, despite an overall increase in overdose rates. CONCLUSIONS: Our study identified gaps in hospital SUD infrastructure during a time of elevated need. Failing to address this gap reflects missed opportunities to engage vulnerable populations, provide linkages to treatment, and prevent complications of substance use.

Substance Use Disorder Program Availability in Safety-Net and Non-Safety-Net Hospitals in the US.

Importance: Safety-net hospitals (SNHs) are ideal sites to deliver addiction treatment to patients with substance use disorders (SUDs), but the availability of these services within SNHs nationwide remains unknown. Objective: To examine differences in the delivery of different SUD programs in SNHs vs non-SNHs across the US and to determine whether these differences are increased in certain types of SNHs depending on ownership. Design, Setting, and Participants: This cross-sectional analysis used data from the 2021 American Hospital Association Annual Survey of Hospitals to examine the associations of safety-net status and ownership with the availability of SUD services at acute care hospitals in the US. Data analysis was performed from January to March 2022. Main Outcomes and Measures: This study used 2 survey questions from the American Hospital Association survey to determine the delivery of 5 hospital-based SUD services: screening, consultation, inpatient treatment services, outpatient treatment services, and medications for opioid use disorder (MOUD). Results: A total of 2846 hospitals were included: 409 were SNHs and 2437 were non-SNHs. The lowest proportion of hospitals reported offering inpatient treatment services (791 hospitals [27%]), followed by MOUD (1055 hospitals [37%]), and outpatient treatment services (1087 hospitals [38%]). The majority of hospitals reported offering consultation (1704 hospitals [60%]) and screening (2240 hospitals [79%]). In multivariable models, SNHs were significantly less likely to offer SUD services across all 5 categories of services (screening odds ratio [OR], 0.62 [95% CI, 0.48-0.76]; consultation OR, 0.62 [95% CI, 0.47-0.83]; inpatient services OR, 0.73 [95% CI, 0.55-0.97]; outpatient services OR, 0.76 [95% CI, 0.59-0.99]; MOUD OR, 0.6 [95% CI, 0.46-0.78]). With the exception of MOUD, public or for-profit SNHs did not differ significantly from their non-SNH counterparts. However, nonprofit SNHs were significantly less likely to offer all 5 SUD services compared with their non-SNH counterparts (screening OR, 0.52 [95% CI, 0.41-0.66]; consultation OR, 0.56 [95% CI, 0.44-0.73]; inpatient services OR, 0.45 [95% CI, 0.33-0.61]; outpatient services OR, 0.58 [95% CI, 0.44-0.76]; MOUD OR, 0.61 [95% CI, 0.46-0.79]). Conclusions and Relevance: In this cross-sectional study of SNHs and non-SNHs, SNHs had significantly lower odds of offering the full range of SUD services. These findings add to a growing body of research suggesting that SNHs may face additional barriers to offering SUD programs. Further research is needed to understand these barriers and to identify strategies that support the adoption of evidence-based SUD programs in SNH settings.

Integrating Harm Reduction into Medical Care: Lessons from Three Models.

BACKGROUND: Substance use disorders (SUDs) are at a national high, with significant morbidity and mortality. Harm reduction, a public-health strategy aimed at reducing the negative consequences of a risky behavior without necessarily eliminating the behavior, represents a useful approach to engage patients with SUDs in care. The objective of this article is to describe how 3 medical practices operationalized harm reduction as a framework toward patient care and identify the common practices undertaken across these settings to integrate harm reduction and medical care. METHODS: We conducted a qualitative study using in-depth, semistructured interviews with 20 staff and providers at 3 integrated harm reduction and medical care sites across New York State from March to June 2021. Interview questions focused on how harm reduction approaches were implemented, how harm reduction philosophies were demonstrated in practice, and barriers to adoption. RESULTS: The interviews resulted in 8 main themes of integrated harm reduction medical care: 1) role of provider as both learner and informer; 2) pragmatic measures of success; 3) collaborative and interdisciplinary care teams; 4) developing a stigma-free culture; 5) creating a comfortable and welcoming physical space; 6) low-threshold care with flexible scheduling; and; 7) reaching beyond the clinic to disseminate harm reduction orientation; and 8) creating robust referral networks to enhance transitions of care. These themes existed at the patient-provider level (#1 to 3), the organizational level (#4 to 6), and the level extending beyond the clinic (#7 to 8). CONCLUSIONS: All 3 sites followed 8 common themes in delivering harm reduction-informed care, most of which are consistent with the broader movement toward patient-centered care. These practices demonstrate how medical providers may overcome some of the barriers imposed by the medical model and successfully integrate harm reduction as an orienting framework toward care delivery.

Exploring Barriers and Facilitators to Integrating a Harm Reduction Approach to Substance Use in Three Medical Settings.

BACKGROUND: Evidence suggests that harm reduction, a public health strategy aimed at reducing the negative consequences of a risky health behavior without requiring elimination of the behavior itself, may be a promising approach for minimizing drug-related harms while engaging individuals with substance use disorders (SUDs) in care. However, philosophical clashes between the medical and harm reduction models may pose barriers to adopting harm reduction approaches within medical settings. OBJECTIVE: To identify barriers and facilitators to implementing a harm reduction approach toward care within healthcare settings. We conducted semi-structured interviews with providers and staff at three integrated harm reduction and medical care sites in New York. DESIGN: Qualitative study using in-depth and semi-structured interviews. PARTICIPANTS: Twenty staff and providers across three integrated harm reduction and medical care sites across New York state. APPROACH: Interview questions focused on how harm reduction approaches were implemented and demonstrated in practice and barriers and facilitators to implementation, as well as questions based on the five domains of the Consolidated Framework for Implementation Research (CFIR). KEY RESULTS: We identified three key barriers to the adoption of the harm reduction approach that surrounded resource constraints, provider burnout, and interacting with external providers that do not have a harm reduction orientation. We also identified three facilitators to implementation, which included ongoing training both within and external to the clinic, team-based and interdisciplinary care, and affiliations with a larger healthcare system. CONCLUSIONS: This study demonstrated that while multiple barriers to implementing harm reduction informed medical care existed, health system leaders can adopt practices to mitigate barriers to adoption, such as value-based reimbursement models and holistic models of care that address the full spectrum of patient needs.

Hospital adoption of harm reduction and risk education strategies to address substance use disorders.

Background: Hospitals are well-positioned to integrate harm reduction into their workflow. However, the extent to which hospitals across the United States are adopting these strategies remains unknown.Objectives: To assess what factors are associated with hospital adoption of harm reduction/risk education strategies, and trends of adoption across time.Methods: We constructed a dataset marking implementation of harm reduction/risk education strategies for a 20% random sample of nonprofit hospitals in the U.S (n = 489) using 2019-2021 community health needs assessments (CHNAs) and implementation strategies obtained from hospital websites. We used two-level mixed effects logistic regression to test the association between adoption of these activities and organizational and community-level variables. We also compared the proportion of hospitals that adopted these strategies in the 2019-2021 CHNAs to an earlier cohort (2015-2018.)Results: In the 2019-2021 CHNAs, 44.7% (n = 219) of hospitals implemented harm reduction/risk education programs, compared with 34.1% (n = 156) in the 2015-2018 cycle. In our multivariate model, hospitals that implemented harm reduction/risk education programs had higher odds of having adopted three or more additional substance use disorder (SUD) programs (OR: 10.5: 95% CI: 5.35-20.62), writing the CHNA with a community organization (OR: 2.14; 95% CI: 1.15-3.97), and prioritizing SUD as a top three need in the CHNA (OR: 2.63; 95% CI: 1.54-4.47.)Conclusions: Our results suggest that hospitals with an existing SUD infrastructure and with connections to community are more likely to implement harm reduction/risk education programs. Policymakers should consider these findings when developing strategies to encourage hospital implementation of harm reduction activities.

Utilizing Publicly Available Community Data to Address Social Determinants of Health: A Compendium of Data Sources.

To compile a compendium of data sources representing different areas of social determinants of health (SDOH) in New York City. We conducted a PubMed search of the peer-reviewed and gray literature using the terms "social determinants of health" and "New York City," with the Boolean operator "AND." We then conducted a search of the "gray literature," defined as sources outside of standard bibliographic databases, using similar terms. We extracted publicly available data sources containing NYC-based data. In defining SDOH, we used the framework outlined by the CDC's Healthy People 2030, which uses a place-based framework to categorize 5 domains of SDOH: (1) healthcare access and quality; (2) education access and quality; (3) social and community context; (4) economic stability; and (5) neighborhood and built environment. We identified 29 datasets from the PubMed search, and 34 datasets from the gray literature, resulting in 63 datasets related to SDOH in NYC. Of these, 20 were available at the zip code level, 18 at the census tract-level, 12 at the community-district level, and 13 at the census block or specific address level. Community-level SDOH data are readily attainable from many public sources and can be linked with health data on local geographic-levels to assess the effect of social and community factors on individual health outcomes.

Association of Medicaid expansion and 1115 waivers for substance use disorders with hospital provision of opioid use disorder services: a cross sectional study.

INTRODUCTION: Opioid-related hospitalizations have risen dramatically, placing hospitals at the frontlines of the opioid epidemic. Medicaid expansion and 1115 waivers for substance use disorders (SUDs) are two key policies aimed at expanding access to care, including opioid use disorder (OUD) services. Yet, little is known about the relationship between these policies and the availability of hospital based OUD programs. The aim of this study is to determine whether state Medicaid expansion and adoption of 1115 waivers for SUDs are associated with hospital provision of OUD programs. METHODS: We conducted a cross-sectional study of a random sample of hospitals (n = 457) from the American Hospital Association's 2015 American Hospital Directory, compiled with the most recent publicly available community health needs assessment (2015-2018). RESULTS: Controlling for hospital characteristics, overdose burden, and socio-demographic characteristics, both Medicaid policies were associated with hospital adoption of several OUD programs. Hospitals in Medicaid expansion states had significantly higher odds of implementing any program related to SUDs (OR: 1.740; 95% CI: 1.032-2.934) as well as some specific activities such as programs for OUD treatment (OR: 1.955; 95% CI: 1.245-3.070) and efforts to address social determinants of health (OR: 6.787; 95% CI: 1.308-35.20). State 1115 waivers for SUDs were not significantly associated with any hospital-based SUD activities. CONCLUSIONS: Medicaid expansion was associated with several hospital programs for addressing OUD. The differential availability of hospital-based OUD programs may indicate an added layer of disadvantage for low-income patients with SUD living in non-expansion states.

Synchronous Home-Based Telemedicine for Primary Care: A Review.

Synchronous home-based telemedicine for primary care experienced growth during the coronavirus disease 2019 pandemic. A review was conducted on the evidence reporting on the feasibility of synchronous telemedicine implementation within primary care, barriers and facilitators to implementation and use, patient characteristics associated with use or nonuse, and quality and cost/revenue-related outcomes. Initial database searches yielded 1,527 articles, of which 22 studies fulfilled the inclusion criteria. Synchronous telemedicine was considered appropriate for visits not requiring a physical examination. Benefits included decreased travel and wait times, and improved access to care. For certain services, visit quality was comparable to in-person care, and patient and provider satisfaction was high. Facilitators included proper technology, training, and reimbursement policies that created payment parity between telemedicine and in-person care. Barriers included technological issues, such as low technical literacy and poor internet connectivity among certain patient populations, and communication barriers for patients requiring translators or additional resources to communicate.

Obesity and Patient Activation: Confidence, Communication, and Information Seeking Behavior.

INTRODUCTION/OBJECTIVES: Patient activation describes the knowledge, skills, and confidence that allow patients to actively engage in managing their health. Prior studies have found a strong relationship between patient activation and clinical outcomes, costs of care, and patient experience. Patients who are obese or overweight may be less engaged than normal weight patients due to lower confidence or stigma associated with their weight. The objective of this study is to examine whether weight status is associated with patient activation and its sub-domains (confidence, communication, information-seeking behavior). METHODS: This repeated cross-sectional study of the 2011 to 2013 Medicare Current Beneficiary Survey (MCBS) included a nationally representative sample of 13,721 Medicare beneficiaries. Weight categories (normal, overweight, obese) were based on body mass index. Patient activation (high, medium, low) was based on responses to the MCBS Patient Activation Supplement. RESULTS: We found no differences in overall patient activation by weight categories. However, compared to those with normal weight, people with obesity had a higher relative risk (RRR 1.24; CI 1.09-1.42) of "low" rather than "high" confidence. Respondents with obesity had a lower relative risk (RRR 0.82; CI 0.73-0.92) of "low" rather than "high" ratings of communication with their doctor. DISCUSSION AND CONCLUSIONS: Though patients with obesity may be less confident in their ability to manage their health, they are more likely to view their communication with physicians as conducive to self-care management. Given the high receptivity among patients with obesity toward physician communication, physicians may be uniquely situated to guide and support patients in gaining the confidence they need to reach weight loss goals.

Health Centers and Value-Based Payment: A Framework for Health Center Payment Reform and Early Experiences in Medicaid Value-Based Payment in Seven States.

Policy Points As essential access points to primary care for almost 29 million US patients, of whom 47% are Medicaid enrollees, health centers are positioned to implement the population health management necessary in value-based payment (VBP) contracts. Primary care payment reform requires multiple payment methodologies used together to provide flexibility to care providers, encourage investments in infrastructure and new services, and offer incentives for achieving better health outcomes. State policy and significant financial incentives from Medicaid agencies and Medicaid managed care plans will likely be required to increase health center participation in VBP, which is consistent with broader state efforts to expand investment in primary care. CONTEXT: Efforts are ongoing to advance value-based payment (VBP), and health centers serve as essential access points to comprehensive primary care services for almost 29 million people in the United States. Therefore, it is important to assess the levels of health center participation in VBP, types of VBP contracts, characteristics of health centers participating in VBP, and variations in state policy environments that influence VBP participation. METHODS: This mixed methods study combined qualitative research on state policy environments and health center participation in VBP with quantitative analysis of Uniform Data System and health center financial data in seven vanguard states: Oregon, Washington, California, Colorado, New York, Hawaii, and Kentucky. VBP contracts were classified into three layers: base payments being transformed from visit-based to population-based (Layer 1), infrastructure and care coordination payments (Layer 2), and performance incentive payments (Layer 3). FINDINGS: Health centers in all seven states participated in Layer 2 and Layer 3 VBP, with VBP participation growing from 35% to 58% of all health centers in these states from 2013 to 2017. Among participating health centers, the average percentage of Medicaid revenue received as Layer 2 and Layer 3 VBP rose from 6.4% in 2013 to 9.1% in 2017. Oregon and Washington health centers participating in Layer 1 payment reforms received most of their Medicaid revenue in VBP. In 2017, VBP participation was associated with larger health center size in four states (P <.05), and higher average number of days cash on hand (P <.05) in three states. CONCLUSIONS: A multilayer payment model is useful for implementing and monitoring VBP adoption among health centers. State policy, financial incentives from Medicaid agencies and Medicaid managed plans, and health center-Medicaid collaboration under strong primary care association and health center leadership will likely be required to increase health center participation in VBP.

Patients' Perspectives on the Shift to Telemedicine in Primary and Behavioral Health Care during the COVID-19 Pandemic.

BACKGROUND: Studies specifically focused on patients' perspectives on telemedicine visits in primary and behavioral health care are fairly limited and have often focused on highly selected populations or used overall satisfaction surveys. OBJECTIVE: To examine patient perspectives on the shift to telemedicine, the remote delivery of health care via the use of electronic information and communications technology, in primary and behavioral health care in Federally Qualified Health Centers (FQHCs) during COVID-19. DESIGN: Semi-structured interviews were conducted using video conference with patients and caregivers between October and December 2020. PARTICIPANTS: Providers from 6 FQHCs nominated participants. Eighteen patients and caregivers were interviewed: 6 patients with only primary care visits; 5 with only behavioral health visits; 3 with both primary care and behavioral health visits; and 4 caregivers of children with pediatric visits. APPROACH: Using a protocol-driven, rapid qualitative methodology, we analyzed the interview data and assessed the quality of care, benefits and challenges of telemedicine, and use of telemedicine post-pandemic. KEY RESULTS: Respondents broadly supported the option of home-based synchronous telemedicine visits in primary and behavioral health care. Nearly all respondents appreciated remote visits, largely because such visits provided a safe option during the pandemic. Patients were generally satisfied with telemedicine and believed the quality of visits to be similar to in-person visits, especially when delivered by a provider with whom they had established rapport. Although most respondents planned to return to mostly in-person visits when considered safe to do so, they remained supportive of the continued option for remote visits as remote care addresses some of the typical barriers faced by low-income patients. CONCLUSIONS: Addressing digital literacy challenges, enhancing remote visit privacy, and improving practice workflows will help ensure equitable access to all patients as we move to a new post-COVID-19 "normal" marked by increased reliance on telemedicine and technology.

Patient Characteristics Associated With Phone Versus Video Telemedicine Visits for Substance Use Treatment during COVID-19.

OBJECTIVES: Although video visits may offer some benefits over the telephone, not all patients may be equipped to access video telemedicine, raising questions surrounding access disparities. The aim of this study is to examine patient characteristics associated with the use of phone versus video-enabled tele-medication for opioid use disorders (MOUD) during COVID-19. METHODS: This study uses data from a nonurban integrated substance use disorder treatment site in New York to examine patient characteristics associated with the modality of tele-MOUD care. The provider did not offer in-person care. Multivariable regression models were used to assess the association between patient's primary mode of tele-MOUD and patient demographic characteristics. Additional analysis of new patient inductions examined associations between mode of tele-MOUD induction and 30-day follow-up receipt. RESULTS: Of the 4557 tele-MOUD encounters, 76.92% were video and 23.08% were telephone visits. Older patients had significantly higher odds of primarily using telephone (odds ratio [OR]: 0.580; 95% confidence interval [CI]: 0.045, 1.115). Patients with higher education (OR: -0.791; 95% CI: -1.418, -0.168), recent overdose (OR: -0.40; 95% CI: -0.793, -0.010), and new patients (OR: 0.484; 95% CI: -0.945, 0.023) were significantly less likely to rely on telephone. Of 336 new patient initiations, 31 were conducted by telephone while 305 were conducted through video. The mode of new patient initiation was not associated with a follow-up visit within 30 days of initiation. CONCLUSIONS: Telemedicine may increase access to MOUD, though certain patients may rely on different forms of telemedicine. Attention must be paid to policies that promote equitable access to both video and telephone tele-MOUD visits.

Racial/ethnic disparities in the availability of hospital based opioid use disorder treatment.

INTRODUCTION: While racial/ethnic disparities in the use of opioid use disorder (OUD) treatment in outpatient settings are well documented in the literature, little is known about racial/ethnic disparities in access to hospital-based OUD services. This study examines the relationship between hospital-based or initiated OUD services and the racial/ethnic composition of the surrounding community. METHODS: We constructed a dataset marking the implementation of eight OUD strategies for a 20% random sample of nonprofit hospitals in the United States based on 2015-2018 community health needs assessments. We tested the significance of the relationship between each OUD strategy and the racial/ethnic composition of the surrounding county using two-level mixed effects logistic regression models that considered the hierarchical structure of the data of hospitals within states while controlling for hospital-level county-level, and state-level covariates. RESULTS: In both unadjusted and adjusted models, we found that hospital adoption of several OUD services significantly varied based on the percentage of Black or Hispanic residents in their communities. Even after controlling for hospital size, the overdose burden in the community, community socioeconomic characteristics, and state funding, hospitals in communities with high percentage of Black or Hispanic residents had significantly lower odds of offering the most common hospital-based programs to address OUD - including programs that increase access to formal treatment services, prescriber guidelines, targeted risk education and harm reduction, and community coalitions to address opioid use. CONCLUSIONS: Hospital adoption of many OUD services varies based on the percentage of Black or Hispanic residents in their communities. More attention should be paid to the role, ability, and strategies that hospitals can assume to address disparities among OUD treatment and access needs, especially those that serve communities with a high concentration of Black and Hispanic residents.

Assessing the effectiveness of problem-solving courts on the reduction of overdose deaths in the United States: A difference-in-difference study.

Background: Criminal justice-involved populations are disproportionately more likely to have an active substance use disorder (SUD) and experience a fatal overdose. One way the criminal justice system connects individuals with SUDs to treatment is through problem-solving drug courts designed to divert offenders into treatment. The aim of this study is to assess the effect of drug court implementation on drug overdoses in U.S counties. Methods: A difference-in-difference analysis of publicly available data on problem-solving courts and monthly, county-level overdose death data, was completed to understand the difference in number of overdose deaths per county per year for counties with a drug court and those without. The time frame was 2000-2012, which included 630 courts serving 221 counties. Results: There was a significant effect of drug courts in reducing county overdose mortality by 2.924 (95% CI: -3.478 - -2.370), after controlling for annual trends. Additionally, having a higher number of outpatient SUD providers in the county (coefficient 0.092, 95% CI: 0.032 - 0.152), a higher proportion of uninsured population (coefficient 0.062, 95% CI: 0.052-0.072), and being in the Northeast region (coefficient 0.51, 95% CI: 0.313 - 0.707), was associated with higher county overdose mortality. Conclusions: When considering responses to SUDs, our findings point towards drug courts as a useful component of a compendium of strategies to address opioid fatalities. Policymakers and local leaders who wish to engage the criminal justice system in efforts to address the opioid epidemic should be aware of this relationship.